A largely incomplete but hopefully useful list of links to datasets for relational learning and inductive logic programming. No guarantees on availability. Symbolic function approximator aims to ...

Abstract: Concept learning is the induction of a description from a set of examples. Inductive logic programming can be considered a special case of the general notion of concept learning specifically ...

The ability to learn programs from few examples is a powerful technology with disruptive applications in many domains, as it allows users to automate repetitive tasks in an intuitive way. Existing ...

Me and another student at Unibo developed a solution entirely written in Prolog to the game proposed in the following website: https://www.codingame.com/training/hard ...

Abstract: The Web has become an extremely large source of information and also a platform of various e-service including e-business, e-science, e-learning, e-government, etc. How to develop the new ...

Inductive logic programming [24] is situated in the intersection of machine learning or data mining on the one hand, and logic programming on the other hand. It shares with the former fields the goal ...

Inductive logic programming (ILP) studies the learning of (Prolog) logic programs and other relational knowledge from examples. Most machine learning algorithms are restricted to finite, propositional ...